Simulation of increasing UV radiation as a consequence of ozone depletion
Bibliographic record
Abstract
UV plays a key roll in several biological functions. As consequence of the ozone depletion investigations to study the effects of UV radiation on human health and terrestrial and aquatic ecosystems have been carried out in laboratories and in the field. Experiments performed in laboratories, irradiating samples with lamps often present the inconvenience that light sources do not reproduce properly the solar spectrum. Field experiments are usually carried out comparing samples exposed to ambient irradiance (normal or increased) against 100% UV-B screened samples. This scenario also differs from the real situation of normal irradiance against UV-B increased irradiance. Some authors have solved this problem performing studies under ambient conditions, simulating the ozone depletion by supplementation of the UV-B radiation with lamps. As part of the IAI CNR-26, "Enhanced Ultraviolet-B Radiation in Natural Ecosystems as an added Perturbation due to Ozone Depletion," mesocosms experiments were performed at Rimouski (Canada), Ubatuba (Brasil) and Ushuaia (Argentina) using the supplementing methodology. In this paper we introduce the design of the measurements and lamps setting and the methodology used to calculate the attenuation constant and the irradiance at the water column at the mesocosms during the experiment, emphasizing on the Ubatuba campaign.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".